200 results about "Generative Design" patented technology

The invention provides a generative adversarial-driven intelligent security defense method and system, and solves the problem of dynamic network security defense through three-layer architecture innovation: 1, data fusion layer reconstruction: employing a multi-modal feature extraction engine driven by an MoE architecture, dynamically allocating computing power resources to a plurality of expert models, and improving the heterogeneous data distillation efficiency; an LLM for fine adjustment in the security field is introduced, a cross-modal semantic similarity matrix is constructed, and the accuracy of unstructured threat intelligence analysis is improved; a second dynamic attack and defense layer is constructed, a GPT-4 architecture attack generator is deployed, and generation of a multi-stage APT attack chain is simulated; a double-agent reinforcement learning framework is designed, and the confrontation training efficiency is improved; upgrading a three-cognitive decision-making layer, constructing a dynamic threat map based on a time sequence diagram neural network, and updating an adjacent matrix in real time; a plurality of agent clusters are deployed, the capabilities of encrypted traffic analysis and attack blocking are improved, and the problems of data layer defects, attack and defense confrontation limitation and decision-making layer bottleneck in the prior art are solved.

The invention provides an interactive system virtual test method and device based on multi-mode cognitive twin bodies. The method comprises the following steps: 1) constructing user cognitive twin: outputting a behavior decision tree with confidence through an adversarial generative network based on population attributes, cognitive preferences and behavior history; 2) creating a dynamic interaction environment: encoding a to-be-tested interface into a semantic graph structure which can be analyzed by a machine, and associating a physical operation constraint rule base; 3) running a multi-agent test: deploying a twin cluster in the virtual sandbox, and recording an operation path, an attention thermodynamic diagram and decision delay; and 4) generating a design defect map, namely, positioning an interface cognitive friction point by comparing the deviation degree of an expected interaction flow and an actual behavior track. According to the method, the problems that a traditional user test period is long and scene coverage is limited are solved, and early interception of interaction risks and design optimization preposition are achieved. The method can be widely applied to high-risk / high-cost / high-cycle test scenes of the man-machine interaction system.

The invention relates to the technical field of gift packaging three-dimensional modeling, and discloses a construction method of a gift box packaging design three-dimensional model. The method comprises the following steps: collecting natural language description, a freehand sketch image and a physical material attribute parameter; analyzing a natural language to construct a design intention map, and analyzing a sketch to generate a geometric feature code; performing knowledge alignment fusion on the two to form enhanced design semantic representation; generating an initial three-dimensional design framework by using a generative design algorithm; material parameters are integrated, compatibility simulation test is carried out, parameter self-adaptive adjustment circulation is started according to a feasibility evaluation report, and component parameters are dynamically optimized; and rendering and outputting a final model. Through deep fusion of multi-modal design information and preposed dynamic optimization of physical attributes, the accuracy of design intention expression and the producibility of a three-dimensional model are improved, and automation and intelligentization of a design process are realized.

Systems and processes enhance cybersecurity by dynamically generating a decoy sub-application that operates parallel to the primary application using generative design and a large language model. The core feature involves real-time anomaly detection within application traffic, utilizing AI to assess threats and orchestrate appropriate responses. Upon identifying potential security threats, the system employs generative design principles to architect a restricted-functionality sub-application, deploying it instantly to engage and analyze the attack vectors without compromising sensitive production data. The sub-application is isolated through software-defined networking, ensuring that its operations do not affect the primary application's functionality. Additionally, sophisticated traffic redirection mechanisms are employed to divert suspicious traffic from the primary to the decoy application, thereby protecting the integrity while allowing detailed threat analysis. This dual-capability system not only safeguards against disruptions but also enhances adaptive security measures through continuous learning and system adjustments.

The invention discloses a digital research and development demand automatic disassembling method based on knowledge reasoning. The method comprises the following steps: gathering multi-source demands, uniformly de-duplicating, and establishing a version baseline; a semantic graph is generated according to the standardized requirements, a support graph and a constraint set are constructed, and a resource portrait, historical measurement and a template library are formed; performing retrieval and sub-graph aggregation by using an improved GraphRAG model, completing alignment reasoning and outputting a fact set, a conflict list and a deletion list; the method comprises the following steps: generating a hierarchical task, dependency and priority by using an improved Reflexion algorithm, and performing shadow scheduling and acyclic verification to obtain an execution sequence table; generating a design / interface / test / verification / acceptance workpiece, and solving resources, milestones and key paths according to the design / interface / test / verification / acceptance workpiece; and a tracing link and an early warning mechanism are established, and rearrangement and resource redistribution are carried out when the time exceeds the limit. According to the method, the schedule forming time is shortened, the reworking and delay risks are reduced, and the workpiece coverage rate, the critical path controllability and the delivery traceability are improved.

Methods, systems, and apparatus, including medium-encoded computer program products, for computer aided design of physical structures include: obtaining a design space, design criteria, and boundary conditions for numerical simulation; defining an application of the boundary conditions to a voxelized mesh, including specifying a distribution of a load to nodes of voxels in the voxelized mesh that correspond to a surface of preserve geometry; and iteratively modifying a generatively designed three dimensional shape in the design space in accordance with the design criteria and a physical response of the modeled object determined by the numerical simulation performed using the application of the boundary conditions to the voxelized mesh, wherein the distribution of the total loading value during determination of the physical response ensures an equivalence between the total loading value and a sum of loading values distributed to the respective nodes of the voxels that correspond to the surface.

A generative machine learning model, such as a convolutional neural network (CNN), can be trained with solutions from a topology optimization solver for a solution for a topology of a set of structures so that the generative machine learning model can generate a plurality of alternative designs for a structure that are alternative topology optimizations (for the structure) for a set of initial setup parameters. The generative model when being trained includes a generative network and a discriminator network. The generative model can be trained using outputs from a CNN autoencoder for densities and a CNN autoencoder for strain energies.

The invention discloses a multi-objective optimization method for the form of an urban block, and the method comprises the following steps: S100, constructing a parameterized model, carrying out the experimental design, defining a group of geometric parameters used for describing the form of the urban block, and generating a plurality of sample points in the value range of the geometric parameters through employing a sampling method; s200, bidirectional coupling numerical simulation is executed, a data set is generated, at least one thermal comfort evaluation index and one air quality evaluation index are output, and therefore the data set containing input parameters and output indexes is formed; step S300, constructing and verifying a machine learning agent model to obtain an agent model capable of rapidly predicting the evaluation index; step S400, executing multi-objective optimization search, and automatically searching to enable the thermal comfort evaluation index and the air quality evaluation index to simultaneously achieve a better Pareto optimal solution set; and step S500, analyzing and outputting an optimization result, extracting an optimization value range of the geometric parameters, and generating a design guide.

Variants of the method can include determining a design, generating a geometric representation of the design, generating a topological representation of the design, determining a context value set, predicting a physical field using a trained physics model, optionally verifying the physical field, optionally generating a corrected physical field, and optionally training the physics model based on the corrected physical field.

The invention relates to the technical field of electric power iron tower full-life-cycle carbon footprint accounting, provides an electric power iron tower full-life-cycle carbon footprint accounting method and system, and aims to solve the problems of low efficiency and poor accuracy of electric power iron tower full-life-cycle carbon footprint accounting in the prior art. The method comprises the steps that an electric power iron tower component library is constructed, and a design stage carbon accounting benchmark is generated in combination with a building information model, a steel model, a welding process and anti-corrosion coating parameters; capturing assembly installation deviation and splicing gaps in real time, calculating material loss caused by construction errors, and converting the material loss into carbon emission increment; loading data by using a digital twinning technology, adjusting a material loss early warning threshold value, and updating design data; based on the corrected data, icing load deformation and corrosion expansion in the operation and maintenance stage are analyzed, and a full-life-cycle carbon footprint report is generated in combination with the updated stress distribution data. According to the technical scheme provided by the invention, the efficiency and accuracy of the full-life-cycle carbon footprint accounting of the electric power iron tower can be improved.

The invention discloses a bridge substructure modeling scheme generation method and device, equipment and a medium, and relates to the technical field of bridge engineering, and the method comprises the steps: obtaining bridge superstructure design input parameters, constructing substructure design task information, and generating design parameters through big language model reasoning; and a modeling script is automatically generated, and structural response calculation is carried out. Different modeling strategies are judged and executed according to the calculation result, finally, a target modeling scheme meeting the requirement is intelligently generated, design parameter generation and automatic modeling of the bridge substructure in a non-standard bridge type scene are achieved, and the design efficiency and accuracy are improved.

The invention relates to the field of motor structure design and optimization, and discloses a cogging torque and torque ripple optimization method for a permanent magnet motor for a vehicle. The method comprises the steps that based on an electromagnetic scheme, a geometric boundary and a term dictionary, a parameterized geometric prototype containing four symmetric semi-arc auxiliary grooves is constructed, and a design variable set structure is generated; converting the structure into a target evaluation interface structure containing a target item and a constraint item; an improved adaptive particle swarm algorithm is combined with finite element rapid check and a new iteration function to carry out optimization solution, and an updated candidate group structure is generated; and finally, optimal parameters are screened through Pareto sorting and robustness recheck, and an engineering configuration structure is generated. According to the method, through systematic parameter modeling, an efficient collaborative optimization algorithm and simulation evaluation, the optimization efficiency and reliability are remarkably improved, the cogging torque and the torque ripple of the motor are effectively reduced, and meanwhile, the process feasibility and the performance robustness of a design scheme are ensured.

The invention relates to a product customization and configuration method and system based on a product model and a knowledge base. The method comprises the following steps: (a) associating a product structure model and a product knowledge base of a target product series; (b) constructing a product configuration model integrating a product structure model, a product knowledge graph and a configuration rule; (c) customer demand parameters are received, and a customized configuration scheme is generated through the product configuration model; (d) automatically generating a design material list and a process material list based on the customized configuration scheme; and (e) executing cost accounting according to the generated design bill of material and the process bill of material and outputting quotation data. The method has the advantages that the requirement of a user for customization can be met, the requirement for configuration can also be met, data such as technologies and processes can be automatically configured for the user, the data can be synchronously updated to related software systems such as PLM and PDM, and the intelligent design and intelligent manufacturing capacity of an enterprise is greatly improved.

The invention relates to the technical field of automobile design, in particular to an intelligent generation type design method of an anti-collision beam, which comprises the following steps: firstly, performing experimental analysis on the anti-collision beam to obtain a section image comprising the anti-collision beam and performance response data corresponding to the section image; performing image recognition and text extraction on the section image; fusing the recognized image and the extracted text by using a multi-modal multi-layer fusion model to obtain a multi-modal design variable; training the constructed conditional variation network by using the multi-modal design variables and the performance response data corresponding to the multi-modal design variables to obtain a conditional variation model; generating design variables by using the conditional variation model, and predicting performance response data corresponding to the variables; optimal performance response data are screened out from the obtained performance response data, and then the optimal design scheme of the anti-collision beam to be designed is obtained. According to the method, the optimal design scheme is determined by using the conditional variation network, and the efficiency and the precision of optimization design are effectively improved.

The invention discloses a jewelry 3D model design method and system. The method comprises the steps of obtaining historical jewelry design full-modal data; carrying out multi-dimensional feature extraction and association labeling on the full-modal data by utilizing computer vision and natural language processing technologies so as to construct a three-dimensional feature matrix; according to the three-dimensional feature matrix, constructing a cross-modal association database through cross-modal structured labeling; generating a multi-modal aesthetic feature database through a multi-task deep learning model by using the cross-modal association database; training a multi-task AI aesthetics evaluation model fusing geometry, styles and user preferences by using the multi-modal aesthetics feature database; and obtaining jewelry 3D design data through the graphical interface, and performing quantitative evaluation of 3D design by using the multi-task AI evaluation model to generate a design evaluation result. Through the design method provided by the invention, the objectivity of jewelry 3D model design evaluation can be improved, so that the design efficiency and the design quality are improved.

The invention discloses a Solar-Think photovoltaic power station intelligent construction platform, and the platform comprises a photovoltaic power station intelligent design module which is used for automatically generating design data; the photovoltaic power station construction collaboration module is used for converting a design model in the design data into a digital twin model, collecting construction data in real time through Internet of Things equipment, and dynamically updating a construction state in a virtual space; the predictive operation and maintenance module is used for predicting equipment faults through an LSTM neural network based on design parameters, construction records and real-time operation and maintenance data of the design model and generating an optimal maintenance path in combination with the digital twinborn model; and the photovoltaic power station full-process data closed-loop architecture module is used for automatically synchronizing the design model to the construction collaboration module, reversely correcting the design model based on construction data, creating association between the construction data and the operation and maintenance data, forming an equipment full-life-cycle file, and transmitting the equipment full-life-cycle file to the construction collaboration module. And feeding back the operation and maintenance data to the design module to support next-generation power station scheme optimization.

The invention provides a reverse generation type design method and system of a battery material based on a large language model. The method comprises the following steps: carrying out serialized representation on a crystal structure of a lithium ion battery material; constructing a material basic model, and training the material basic model based on the serialized representation result to obtain a trained material basic model; a multi-dimensional attribute virtual KV attention mechanism is introduced into the material basic model, and a property conditional generation model is obtained; accessing a property prediction head network to the material basic model, and performing supervised training on the material basic model to obtain a material property prediction model; and performing reinforcement learning training on the property conditional generation model to obtain an optimized property conditional generation model, and generating a crystal structure candidate set based on the optimized property conditional generation model. By means of the method, efficient, controllable and diversified generation of the hundred-atomic-scale complex crystal structure is achieved, and the precision and practicability of material reverse design are remarkably improved.

The invention relates to the technical field of offshore wind power equipment, and discloses an offshore floating type wind turbine mooring system optimization method based on a proxy model, and the method comprises the following steps: S1, determining key design parameters; s2, sampling to generate design points; s3, establishing a total index function of multi-target coupling; s4, generating a sample database through numerical simulation; s5, constructing an agent model by using a Kriging method; s6, calling the proxy model to search an optimal solution by adopting a differential evolution algorithm; s7, performing numerical simulation verification on the optimal solution and judging convergence; and S8, if not, updating the database and returning to S5 for iteration, and if so, outputting the optimal configuration. According to the method, the problems that a traditional optimization method is high in simulation calculation cost and too long in consumed time are solved, searching is carried out through the proxy model instead of high-precision simulation, the verification iteration step is combined, the optimization efficiency is greatly improved while the result accuracy is guaranteed, and the multi-target mooring scheme with the optimal comprehensive performance can be efficiently obtained.

Systems and methods for generating UI designs using deep learning and automated front-end code generation includes training a deep learning model on a dataset of existing UI designs; receiving user parameters and constraints for generating a quick UI design; generating a quick UI design using the trained deep learning model and user-provided parameters and constraints; providing a visual editor for the user to edit the quick UI design into a finished UI design; and generating human-readable front-end code from the finished UI design.

The invention discloses a design parameter collaborative management method and device for a BIM platform, and relates to the technical field related to BIM, and the method comprises the steps: importing a forward design scheme of a thermal power plant into the BIM platform, and generating a design model; performing multi-dimensional accident tracing according to the design model to obtain an accident association map; obtaining a design adjustment space based on the demand and the map adjustment scheme; performing multi-dimensional risk prediction based on the BIM platform and the risk model to generate a risk prediction map; optimizing the adjustment space based on the prediction map and the risk constraint; through disturbance injection optimization, a final forward design optimization result is obtained, so that the technical problems of low design efficiency and difficulty in guaranteeing design quality caused by dispersed design parameters and insufficient collaboration of the thermal power plant in the forward design process of the traditional thermal power plant are solved, and multi-dimensional accident fitting tracing, risk prediction, optimization and other means are realized. The collaborative management level and design quality of the forward design parameters of the thermal power plant are improved, and the accident risk is reduced.

The invention relates to the technical field of electric power engineering, in particular to an electric power construction acceptance method and system based on an image processing technology, and the method comprises the steps: receiving an electric power construction drawing, recognizing an electric power equipment mark and an association mark through a deep neural network, and generating a design parameter set; a multi-view depth image of a construction site is collected, point cloud data and topology rules are fused to construct a live-action three-dimensional model, and an actual measurement parameter set is extracted; carrying out space coordinate system alignment on the design space coordinates and the actually measured space coordinates, calculating size and angle deviations and forming a comprehensive deviation data set; and performing compliance judgment according to a safety threshold value of the power equipment, marking a standard exceeding position, generating a deviation thermodynamic diagram, generating a dynamic rectification scheme in combination with a historical acceptance database and construction environment information, and finally outputting a power acceptance report containing the thermodynamic diagram and rectification suggestions. According to the invention, automatic identification and intelligent rectification of the power construction deviation can be realized, and the acceptance efficiency and the quality traceability are improved.

The invention relates to the technical field of data security, can be applied to business scenes of financial science and technology, medical health and the like, and discloses a security processing method, device and equipment oriented to software development and a medium. Obtaining an architecture design document to identify potential safety hazards and generate design improvement suggestions; generating a code based on the business logic description and the design improvement suggestion, and completing security detection and repair to obtain a processed code and a code repair record; performing security test on the processed code and recording a test result; collecting data of exception identification, hidden danger identification, code detection and repair and security test to update the security knowledge base; and generating a security analysis report based on the demand exception list, the design improvement suggestion, the code repair record and the test result. According to the invention, through a security identification and restoration process from demand to test, early discovery of security problems, linkage processing and knowledge self-updating are realized.

The invention relates to the technical field of data processing, and discloses a building structure automatic design method and system based on artificial intelligence. The method comprises the steps that a collaborative building information model is constructed by collecting building design task data, load analysis and rigidity parameter calculation are carried out, a Timoshenko beam model is constructed, a structural arrangement prediction result is generated in combination with graph network optimization, a parameterized modeling program is input to generate a building structure model, and multi-working-condition analysis is completed to obtain a structural design scheme. Design documents and construction information are automatically generated, and a parameter and analysis result corresponding relation database is established. By integrating modeling, structural analysis and design document generation, the problems of intelligent collaboration and efficient output in the whole process of structural design are effectively solved.

The invention provides a building model construction method based on generative design, a building model and a system. The method comprises the steps that candidate building space units and candidate building components are selected from a building space information model based on a preset space unit generation rule and a preset component generation rule; analyzing the preset space unit generation rule and the preset component generation rule to generate a building space sub-model and a building component sub-model; and on the basis of a constraint relationship between the at least one preset space unit generation rule and the at least one preset component generation rule, splicing the at least one building space sub-model and the at least one building component sub-model into a to-be-constructed target. According to the embodiment of the invention, in the process of constructing the to-be-constructed target, the design process logic is recorded, so that the structuring degree of the to-be-constructed target is relatively high; and the design process logic can be used for training an artificial intelligence model, so that the working efficiency of the user is improved.

Embodiments of the present disclosure provide a system for automatically generating design rule checking (DRC) code for a design rule. The DRC code is generated using a first large-language model (LLM) agent and a second LLM agent. The first LLM agent generates a plurality of design rule conditions based on a multi-modal description of the design rule. The second LLM agent generates executable DRC code based on the plurality of design rule conditions. The executable DRC code is executed on example layouts to generate corresponding outputs. The executable DRC code is evaluated by comparing the outputs with corresponding reference outputs. The executable DRC code is iteratively regenerated based on the evaluation, where the evaluation includes providing a performance report to the first LLM agent and / or to the second LLM agent.

The invention relates to a method for estimating a lifetime curve of at least one technical component, in particular a vehicle assembly or a vehicle component, comprising the following method steps: - Generating design data (350) for at least one technical component with a multitude of parameters and / or settings and / or properties of the technical component, - Transforming the design data (350) into a quantum state (450) by a quantum processor (430), wherein the quantum state (450) comprises each parameter, each parameter value, each property, each property value, each setting and each setting value of the engineering component as a single state (455); - Applying at least one quantum algorithm (470) to the quantum state (450), wherein the quantum algorithm (470) includes at least one quantum amplitude estimation; - Determining relevant states (490) from measurements of the quantum state (450), - Performing simulations with the relevant states (490) to model simulation results (570); - Analyzing the simulation results (570) and calculating a lifetime curve (580) for the technical component; - Output of the lifetime curve (580) as output data (750) for use in adapting the technical component.

An acetabular bone defect filling block design method based on a force conduction path comprises the steps that a mechanical conduction target path is determined, specifically, the stress condition of a hip joint in a gait cycle is simulated on the basis of a three-dimensional model of a pelvis of a patient, a bone defect area Vdefect and a three-dimensional model of an implanted supporting bracket which are obtained in advance, and the mechanical conduction target path is determined; determining an expected force flow conduction path from the acetabular cup loading area to the host bone main bearing area; a filling space determining step: calculating a residual defect space Vremain formed after the support is implanted; a filling block main body generation step: taking the residual defect space Vremain as a design boundary, taking following of the expected force flow conduction path and realization of matching of the structural rigidity and the host bone as an optimization target, generating a filling block main body three-dimensional model with an internal support truss through a topological optimization algorithm, and steering a strong gluteus column by depending on an incomplete acetabular ring, and a fixed foundation which cannot be shaken is provided. An intelligent structure with the optimal mechanical property is generated by converting empirical shape matching into simulation driving generation type design.

Described herein is a computer implemented method, a system and non-transitory computer readable memory for automatically generating a design. The method includes receiving an input prompt for generating the design and generating a design background based at least on the input prompt and a seed design template. The method further includes generating design text based at least on the input prompt; generating a design record including an identifier of the generated design background and the generated design text; and causing the design to be displayed on a client device, the design rendered based on the design record.

Technology is disclosed for constructing a photonic cooling device for a heat source. In one aspect, a computing unit (i) based on at least one design parameter for an extractor layer of the photonic cooling device, inversely designs a coupler layer in accordance with one or more coupler objectives to define a structure of the coupler layer, (ii) generates a coupler-layer design plan indicative of the structure of the coupler layer that facilitates its fabrication, (iii) based on the at least one extractor-layer design parameter, inversely designs a back-reflector layer in accordance with one or more back-reflector objectives to define a structure of the back-reflector layer, (iv) generating a back-reflector-layer design plan indicative of the structure of the back-reflector layer that facilitates its fabrication, and (v) causing at least one of the coupler layer or the back-reflector layer to be fabricated in accordance with the corresponding generated design plan.